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Found 75 Skills
High-performance Quarkus framework expertise covering reactive patterns, CDI, build-time augmentation, and cloud-native development. Use for general Quarkus questions.
Expert service mesh architect specializing in Istio, Linkerd, and cloud-native networking patterns. Masters traffic management, security policies, observability integration, and multi-cluster mesh con
The Fifteen-Factor App methodology for modern cloud-native SaaS applications. This skill should be automatically invoked when planning SaaS tools, product software architecture, microservices design, PRPs/PRDs, or cloud-native application development. Extends the original Twelve-Factor App principles with three additional factors (API First, Telemetry, Security). Trigger keywords include "fifteen factor", "12 factor", "SaaS architecture", "cloud-native design", "application architecture", "microservices best practices", or when in a planning/architecture session.
Guide for implementing HolmesGPT - an AI agent for troubleshooting cloud-native environments. Use when investigating Kubernetes issues, analyzing alerts from Prometheus/AlertManager/PagerDuty, performing root cause analysis, configuring HolmesGPT installations (CLI/Helm/Docker), setting up AI providers (OpenAI/Anthropic/Azure), creating custom toolsets, or integrating with observability platforms (Grafana, Loki, Tempo, DataDog).
The Twelve-Factor App methodology for building scalable, maintainable cloud-native applications. Use when designing backend services, APIs, microservices, or any software-as-a-service application. Triggers on deployment patterns, configuration management, process architecture, logging, and infrastructure decisions.
Vulcan C# Agent — sviluppo C# moderno, cloud-native (AWS/Azure) e provider-agnostic con Serilog, LiteDB, MongoDB e pattern architetturali puliti
Comprehensive geospatial science skill covering remote sensing, GIS, spatial analysis, machine learning for earth observation, and 30+ scientific domains. Supports satellite imagery processing (Sentinel, Landsat, MODIS, SAR, hyperspectral), vector and raster data operations, spatial statistics, point cloud processing, network analysis, cloud-native workflows (STAC, COG, Planetary Computer), and 8 programming languages (Python, R, Julia, JavaScript, C++, Java, Go, Rust) with 500+ code examples. Use for remote sensing workflows, GIS analysis, spatial ML, Earth observation data processing, terrain analysis, hydrological modeling, marine spatial analysis, atmospheric science, and any geospatial computation task.
AWS, GCP, Azure services and cloud-native development
Set up and manage local Kubernetes clusters using KIND (Kubernetes IN Docker). Use when testing Kubernetes applications locally or developing cloud-native workloads.
Provides production-ready Kubernetes manifest guidance including resource management, security, high availability, and configuration best practices. This skill should be used when working with Kubernetes YAML files, deployments, pods, services, or when users mention k8s, container orchestration, or cloud-native applications.
Implement applications using Google Cloud Platform (GCP) services. Use when building on GCP infrastructure, selecting compute/storage/database services, designing data analytics pipelines, implementing ML workflows, or architecting cloud-native applications with BigQuery, Cloud Run, GKE, Vertex AI, and other GCP services.
Micronaut framework guardrails, patterns, and best practices for AI-assisted development. Use when working with Micronaut projects, or when the user mentions Micronaut. Provides compile-time DI, HTTP server/client, data access, and cloud-native guidelines.